Since the widespread acceptance of the Internet, advertising as a main source of revenue has proven to be both effective and lucrative. Advertising on the Internet provides the additional benefit of allowing advertisers to more effectively target audiences viewing their advertisements as opposed to traditional print and “hard copy” advertising which constitute a one-way flow of information: advertisers to users.
The business of Web search, a $10 billion industry, relies heavily on sponsored search, which involves displaying one or more selected paid advertisements alongside algorithmic search results. To maximize long-term revenue, the selection of advertisements should be relevant to the user's query. On the other hand, identifying relevant ads is challenging because the typical query is short and also because users, consciously or not, choose terms intended to lead to optimal Web search results and not to optimal ads. Furthermore, the ads themselves are short and usually formulated to capture the reader's attention rather than to facilitate query matching.
Traditionally, the matching of ads to queries has been accomplished by requiring advertisers to pre-define the queries (“bid phrases”) for which it would be desirable to display a given ad. This approach, however, restricts the ad distribution to a relatively small set of queries. Accordingly, to go beyond this set while maintaining ad relevancy, systems, methods and computer program products are needed that expand an original query with features prevalent among the returned web search results, rewrites of the original query and other features of the original query, using the expanded query to search an advertisement space.